Embodiments of the present invention relate to imaging, and more particularly to predictive autofocusing of an imaging device.
Prevention, monitoring and treatment of physiological conditions such as cancer, infectious diseases and other disorders call for the timely diagnosis of these physiological conditions. Generally, a biological specimen from a patient is used for the analysis and identification of the disease. Microscopic analysis is a widely used technique in the analysis and evaluation of these samples. More specifically, the samples may be studied to detect presence of abnormal numbers or types of cells and/or organisms that may be indicative of a disease state. Automated microscopic analysis systems have been developed to facilitate speedy analysis of these samples and have the advantage of accuracy over manual analysis in which technicians may experience fatigue over time leading to inaccurate reading of the sample. Typically, samples on a slide are loaded onto a microscope. A lens or objective of the microscope may be focused onto a particular area of the sample. The sample is then scanned for one or more objects of interest. It may be noted that it is of paramount importance to properly focus the sample/objective to facilitate acquisition of images of high quality.
Digital optical microscopes are used to observe a wide variety of samples. Rapid autofocusing is important in automated biological and biomedical applications such as high-throughput pharmaceutical screening and large-scale autonomous microrobotic cell manipulation. Rapid autofocusing is also important in other applications such as integrated circuit chip inspection and microassembly of hybrid microelectromechanical systems (MEMS). Thus, rapid autofocusing is highly desirable in real-time image acquisition applications that cannot afford considerable time delays to adjust the focal distance between snapshots of the sample.
Conventional imaging devices perform autofocusing by directing a laser beam at the sample, measuring a reflection of the laser beam off the sample to provide a single reference point, and using a feedback loop to adjust the focal distance. Although this approach may provide rapid autofocusing, the single reference point may lack sufficient information for accurate autofocusing. Certain other presently available techniques also perform autofocusing by obtaining multiple images of a stationary sample at multiple focal distances, determining an optimal focal distance for each of the images and using a feedback loop to adjust the focal distance. Although this approach may provide more accurate autofocusing than the use of a laser beam, acquisition of the numerous images often creates time delays that prevent rapid autofocusing.
Moreover, in order to meet the scan speed requirements for digital slide scanners, autofocus calculations and adjustments may be performed while the stage is in continuous motion. In such cases, certain factors, such as, but not limited to, repeatable variations associated with the scanning stage and/or the sample may negatively influence the focus prediction resulting in unfocused images.
It may therefore be desirable to develop a robust technique and system configured to perform accurate rapid autofocusing in real-time image acquisition applications that advantageously facilitate enhanced scanning speed, while simultaneously maintaining image quality. Moreover, there is a need for a system that is configured to account for mechanical variations while performing accurate rapid autofocusing in real-time image acquisition applications.